Senior Data Engineer / AI ML Engineer with Python, AI/ML & LLMs

Overview In this role you will design and build scalable data pipelines and ML workflows, enabling production-grade AI systems. You will collaborate with data scientists, ML engineers, and developers to create robust data infrastructure powering intelligent applications. You’ll integrate LLMs and support model training, evaluation, and deployment while ensuring data quality and governance. This is an opportunity to shape AI/ML infrastructure in a hybrid Reston-based environment. ResponsibilitiesDesign, build, and maintain scalable ETL/ELT pipelines using Python and modern data engineering toolsCollaborate with AI/ML teams to support model training, evaluation, and deployment workflowsDevelop and optimize data schemas, storage solutions, and APIs for structured and unstructured dataIntegrate and fine-tune LLMs (e.g., OpenAI, Hugging Face Transformers) for various business use casesEnsure data quality, governance, and compliance across all data systemsMonitor and troubleshoot data workflows and model performance in productionAutomate data ingestion from diverse sources including APIs, databases, and cloud storageContribute to the development of internal tools and libraries for ML experimentation and deployment Key requirementsBachelor’s or Master’s degree in Computer Science, Data Engineering, or related field3 years of experience in data engineering or backend developmentStrong proficiency in Python and libraries such as Pandas, NumPy, PySpark, etc.Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)Hands-on experience with LLMs and NLP tools (e.g., LangChain, Hugging Face, OpenAI API)Proficiency in SQL and working with relational and NoSQL databasesFamiliarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)Knowledge of CI/CD pipelines and version control (Git)PythonPandasNumPyPySparkTensorFlowPyTorch